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ProbRadarM3F: mmWave Radar based Human Skeletal Pose Estimation with Probability Map Guided Multi-Format Feature Fusion
However, mmWave radar relies on the collection of reflected signals from the target, and the radar signals containing information is difficult to be fully applied.
SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar
Additionally, KDE helps alleviate point cloud sparsity by capturing density features.
LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion
They are sent to the core of LXL, called "radar occupancy-assisted depth-based sampling", to aid image view transformation.
Contrastive Learning for Automotive mmWave Radar Detection Points Based Instance Segmentation
Deep learning-based instance segmentation enables real-time object identification from the radar detection points.
Deep Instance Segmentation with Automotive Radar Detection Points
Automotive radar provides reliable environmental perception in all-weather conditions with affordable cost, but it hardly supplies semantic and geometry information due to the sparsity of radar detection points.
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